Detection of small objects under an autonomous vehicle chassis

ABSTRACT

An autonomous vehicle includes an under-chassis object detection system for identifying the presence of an object on a road that the autonomous vehicle is travelling upon. The under-chassis object detection system may include a LIDAR system. The object on the road that the autonomous vehicle is travelling upon is of a size that allows the vehicle&#39;s chassis to pass over the object on the road. The autonomous vehicle may react to the detected object on the road to operate the autonomous vehicle safely, such as by altering the vehicle&#39;s trajectory, by stopping the vehicle, or by communicating with a control center for further instructions.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to provisional application No.63/105,699, titled “DETECTION OF SMALL OBJECTS UNDER AN AUTONOMOUSVEHICLE CHASSIS,” filed Oct. 26, 2020, the disclosures of which arehereby incorporated by reference herein.

TECHNICAL FIELD

The present disclosure relates generally to autonomous vehicles. Moreparticularly, the present disclosure is related to detecting andreacting to objects of a size that allows a chassis of an autonomousvehicle to pass over the object on a road over which the autonomousvehicle is travelling.

BACKGROUND

One aim of autonomous vehicle technologies is to provide vehicles thatcan safely navigate towards a destination with limited or no driverassistance. In some cases, an autonomous vehicle may encounter objectsof a size that allows a chassis of the autonomous vehicle to pass overthe object on the road which the autonomous vehicle is travelling.Currently in such cases, sensors placed to allow an autonomous vehicleto navigate roads may not detect objects close to the surface of theroad, possibly endangering the autonomous vehicle when it drives oversuch small objects.

SUMMARY

Detection of small objects that may fit under a vehicle's chassis isimportant for the operation of an autonomous vehicle to compliance withthe law, as well as to ensure the safety of persons and propertysurrounding the autonomous vehicle. Systems and methods are describedherein that allow an autonomous vehicle to detect the presence of smallobjects on the road over which the autonomous vehicle is travelling andadjust trajectory or velocity to ensure safe operation of the autonomousvehicle.

A system is provided that includes an autonomous vehicle (AV). Theautonomous vehicle includes: an under-chassis object detectionsubsystem; an in-vehicle control computer with an under-chassis objectdetection module; and an autonomous control subsystem.

The following features may be present in the system in any reasonablecombination. The autonomous vehicle may include a tractor-trailer andthe under-chassis object detection subsystem includes a sensor mountedunder the fifth wheel of a tractor portion of the tractor-trailer. Insuch implementations, the sensor may include any of a LIDAR unit, aradar unit, and a camera. The under-chassis object detection subsystemincludes one or more sensors with a detection area that includes part ofan area of road under a chassis of the autonomous vehicle. In suchimplementations, the one or more sensors of the under-chassis objectdetection subsystem includes any of: a LIDAR unit, a radar unit, and acamera. The system may include a driving operation module configured toreceive data from the under-chassis object detection module and plantrajectory changes for the autonomous vehicle in response to objectsdetected and identified as hazardous by the under-chassis objectdetection module. The system may further include one or more vehiclecontrol subsystems, each vehicle control subsystem configured to acceptoperating commands from the driving operation module, the one or morevehicle control subsystems comprising any of: an engine power outputunit, a braking unit, a navigation unit, a steering unit, and anautonomous control unit. An autonomous control unit may be part of thesystem, and the autonomous control unit may be configured to: accepthazard information from the under-chassis object detection module; plantrajectory changes for the autonomous vehicle in response to the hazardinformation; and send operating commands to one or more vehicle controlsubsystems that include any of: an engine power output unit; a brakingunit; a navigation unit; and a steering unit.

Provided in some implementations is a method that includes: sensing, bya sensor of an under-chassis object detection subsystem, an object on aroad that an autonomous vehicle is travelling upon; transmitting, by theunder-chassis object detection subsystem, data from the sensor to anin-vehicle control computer; and determining, by an under-chassis objectdetection module of the in-vehicle control computer, the presence of anobject on the road, the object being of a size that allows a chassis ofthe autonomous vehicle to pass over the object on the road.

The following features may be part of the method in any reasonablecombination. The method may further include modifying the trajectory orroute of the autonomous vehicle to account for the presence of theobject on the road. Determining a hazard level for the object on theroad determined by the under-chassis object detection module may be partof the method. Such methods may include modifying the trajectory orroute of the autonomous vehicle to account for the hazard level for theobject on the road determined by the under-chassis object detectionmodule. Determining a hazard level for the object on the road mayinclude: determining a certainty value for the identification of theobject on the road; sending data to an oversight system when thecertainty value is below a threshold value; and identifying, by theoversight system, the object on the road with certainty. In suchimplementations, identifying the object on the road with certainty mayinclude a determination by a human remote control operator (RCO);alternatively or additionally, identifying the object on the road mayinclude receiving a determination from a human remote control operator.Determining a hazard level for the object on the road may include:determining, by the under-chassis detection module, that the identifiedobject on the road is larger than a predetermined threshold size;determining, by the under-chassis detection module, that the identifiedobject on the road is situated in a position that requires a change intrajectory by the autonomous vehicle; and determining, by theunder-chassis detection module, that the identified object on the roadis sharp, jagged, or otherwise a potential cause of a puncture or otherdamage to an underside of the autonomous vehicle or any tires of theautonomous vehicle. The method may include causing the autonomousvehicle to operate according to a determined course of action that isbased on the determined hazard level for the object on the road. Themethod may include causing the autonomous vehicle to execute themodified trajectory or route that is based on the presence of the objecton the road.

In some implementations, an autonomous vehicle is provided that includesan in-vehicle computing unit that has at least one processor and atleast one memory. The at least one memory includes instructions which,when executed by the at least one processor, cause the at least oneprocessor execute the method, as described herein. The autonomousvehicle may also include vehicle sensor subsystems with theunder-chassis object detection subsystem; an autonomous control unit;and a means for network communications. Additionally, or alternatively,provided herein embodiments of an autonomous vehicle that includes anin-vehicle computing unit comprising at least one processor and at leastone memory that include instructions which, when executed by the atleast one processor, cause the at least on processor to execute amethod. In such embodiments, the method includes sensing, by a sensor ofan under-chassis object detection subsystem, an object on a road that anautonomous vehicle is travelling upon; transmitting, by theunder-chassis object detection subsystem, data from the sensor to thein-vehicle control computer; and determining, by an under-chassis objectdetection module of the in-vehicle control computer, the presence of anobject on the road, the object being of a size that allows a chassis ofthe autonomous vehicle to pass over the object on the road. The at leastone memory of the autonomous vehicle may further include modifying thetrajectory or route of the autonomous vehicle to account for the objecton the road; and determining a hazard level for the object on the roaddetermined by the under-chassis object detection module.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of this disclosure, reference is nowmade to the following brief description, taken in connection with theaccompanying drawings and detailed description, wherein like referencenumerals represent like parts.

FIG. 1A illustrates a schematic diagram of a system including anautonomous vehicle;

FIG. 1B illustrates an autonomous vehicle with an under-chassisdetection subsystem including at least one sensor;

FIG. 2 shows a flow diagram for operation of an autonomous vehicle (AV)safely in light of the health and surroundings of the AV;

FIG. 3 illustrates a system that includes one or more autonomousvehicles, a control center or oversight system with a human operator(e.g., a remote center operator (RCO)), and an interface for third-partyinteraction; and

FIG. 4 shows a flow diagram for operation of an autonomous vehicle (AV)with an under-chassis object detection system.

DETAILED DESCRIPTION

Vehicles traversing highways and roadways need to be aware ofsurrounding vehicles and obstacles. Described below in detail aresystems and methods for the safe and lawful operation of an autonomousvehicle on a roadway, including the detection of small objects on aroadway over which the autonomous vehicle is travelling.

Autonomous Truck

FIG. 1A shows a system 100 that includes a tractor 105 of an autonomoustruck. The tractor 105 includes a plurality of vehicle subsystems 140and an in-vehicle control computer 150 The plurality of vehiclesubsystems 140 includes vehicle drive subsystems 142, vehicle sensorsubsystems 144, and vehicle control subsystems. An engine or motor,wheels and tires, a transmission, an electrical subsystem, and a powersubsystem may be included in the vehicle drive subsystems. The engine ofthe autonomous truck may be an internal combustion engine, a fuel-cellpowered electric engine, a battery powered electrical engine, a hybridengine, or any other type of engine capable of moving the wheels onwhich the tractor 105 moves. The tractor 105 may have multiple motors oractuators to drive the wheels of the vehicle, such that the vehicledrive subsystems 142 include two or more electrically driven motors. Thetransmission may include a continuous variable transmission or a setnumber of gears that translate the power created by the engine into aforce that drives the wheels of the vehicle. The vehicle drivesubsystems may include an electrical system that monitors and controlsthe distribution of electrical current to components within the system,including pumps, fans, and actuators. The power subsystem of the vehicledrive subsystem may include components that regulate the power source ofthe vehicle.

Vehicle sensor subsystems 144 can include sensors for general operationof the autonomous truck 105 and an under-chassis object detectionsubsystem 145. The sensors for general operation of the autonomousvehicle may include cameras, a temperature sensor, an inertial sensor(IMU), a global positioning system, a light sensor, a LIDAR system, aradar system (radio detection and ranging system), and a wirelesscommunications system.

At least one sensor is associated with the under-chassis objectsubsystem 145. The sensor or sensors may be mounted specifically on theoutside of the tractor portion of an autonomous truck 105. A LIDARsystem (light detection and ranging system or a laser detection anranging system) may be included in the sensor or sensors of theunder-chassis object subsystem 145. Ideally, the sensor(s) of theunder-chassis object subsystem 145 are mounted under a fifth wheel ofthe tractor portion of the autonomous truck 105. Alternatively, oradditionally, the at least one sensor of the under-chassis objectsubsystem 145 may include a LIDAR system, a radar system, an ultrasonicsensor, or a camera. The sensor(s) of the under-chassis object subsystem145 may be mounted to other locations on the tractor portion of theautonomous truck 105 in addition to, or in place of, under the fifthwheel or location where the tractor and trailer portions of theautonomous truck 105 are joined or connected. Such alternative mountinglocations may include parts of the chassis of the tractor portion of theautonomous truck 105. FIG. 1B shows an autonomous truck 105 with anunder-chassis object subsystem 145 located under the chassis 106 of thetractor portion of the autonomous truck, under the fifth wheel 110. Thefifth wheel is generally located at the rear portion of a tractor and iswhere the trailer connects, or hitches, to the tractor. In someimplementations, the under-chassis object subsystem may include sensorsplaced in other strategic locations on the chassis or portions of thevehicle body that are road-facing. Such locations may include those thatare not impeded by the wheels or axels. The term under-chassis, as usedherein may refer to any area beneath the chassis of a vehicle, such asan autonomous truck, or the area including the road-facing portions of avehicle down to the surface over which the vehicle may travel (or istravelling). In some implementations, the area encompassed by the termunder-chassis may include the area beneath a vehicle and extend beyondthe front-end, rear-end, and sides of the vehicle, depending on thedetection capabilities of sensors used in an under-chassis objectdetection subsystem.

The vehicle control subsystem 146 may be configured to control operationof the autonomous vehicle, or truck, 105 and its components.Accordingly, the vehicle control subsystem 146 may include variouselements such as an engine power output subsystem, a braking unit, anavigation unit, a steering system, and an autonomous control unit. Theengine power output may control the operation of the engine, includingthe torque produced or horsepower provided, as well as provide controlthe gear selection of the transmission. The braking unit can include anycombination of mechanisms configured to decelerate the autonomousvehicle 105. The braking unit can use friction to slow the wheels in astandard manner. The braking unit may include an Anti-lock brake system(ABS) that can prevent the brakes from locking up when the brakes areapplied. The navigation unit may be any system configured to determine adriving path or route for the autonomous vehicle 105. The navigationunit may additionally be configured to update the driving pathdynamically while the autonomous vehicle 105 is in operation. In someembodiments, the navigation unit may be configured to incorporate datafrom the satellite-based global positioning device (e.g., GPS device)and one or more predetermined maps so as to determine the driving pathfor the autonomous vehicle 105. The steering system, or unit, mayrepresent any combination of mechanisms that may be operable to adjustthe heading of autonomous vehicle 105 in an autonomous mode or in adriver-controlled mode.

The autonomous control unit may represent a control system configured toidentify, evaluate, and avoid or otherwise negotiate potential obstaclesin the environment of the autonomous vehicle 105. In general, theautonomous control unit may be configured to control the autonomousvehicle 105 for operation without a driver or to provide driverassistance in controlling the autonomous vehicle 105. In someembodiments, the autonomous control unit may be configured toincorporate data from the GPS device, the RADAR, the LIDAR, the cameras,and/or other vehicle subsystems to determine the driving path ortrajectory for the autonomous vehicle 105.

An in-vehicle control computer 150, which may be referred to as a VCU,includes a vehicle subsystem interface 160, a driving operation module168, one or more processors 170, an under-chassis object detectionmodule 165, a memory 175, and a network communications subsystem 178.This in-vehicle control computer 150 controls many, if not all, of theoperations of the autonomous truck 105 in response to information fromthe various vehicle subsystems 140. The one or more processors 170execute the operations associated with the under-chassis objectdetection module 165 that allow the system to determine that theautonomous vehicle may pass over a small object, such as road debris,traffic cones, and other objects of a size that allows the vehicle'schassis to pass over the object while the vehicle is on the road. Theunder-chassis object detection module 165 may also be able to identifyirregularities in the road surface including cracks, potholes, and thelike. Data from the under-chassis object detection subsystem 145 isprovided to the under-chassis object detection module 165 so that thedetermination of authorities can be made. The under-chassis objectdetection module 165 may in turn determine what course of action shouldbe taken by the autonomous truck 105. Alternatively, or additionally,the under-chassis object detection module 165 may pass data orinformation to the driving operation module 168, memory 175, orprocessors 170. Data from other vehicle sensor subsystems 144 isprovided to the driving operation module 168 in addition to theinformation from the under-chassis object detection module 165 todetermine a course of action to be taken when an object small enough topass under the vehicle is encountered.

A course of action that an autonomous truck 105 can take in response toan object on the road surface may depend on the type of object detected.A size threshold may be applied that will dictate when the autonomoustruck will change lanes or slow to avoid an object on the road.Alternatively, or additionally, a location criteria may be applied tothe detected small object on the road which may cause the autonomoustruck to slow down or change lanes. Once an object is detected, thein-vehicle control computer 150 may classify the identified object intodifferent hazard levels. Each hazard level may require a different typeof control protocol or behavior from the autonomous truck 105.

The memory 175 may contain additional instructions as well, includinginstructions to transmit data to, receive data from, interact with, orcontrol one or more of the vehicle drive subsystem 142, the vehiclesensor subsystem 144, and the vehicle control subsystem 146. Thein-vehicle control computer (VCU) 150 may control the function of theautonomous vehicle 105 based on inputs received from various vehiclesubsystems (e.g., the vehicle drive subsystem 142, the vehicle sensorsubsystem 144, and the vehicle control subsystem 146). Additionally, theVCU 150 may send information to the vehicle control subsystems 146 todirect the trajectory, velocity, signaling behaviors, and the like, ofthe autonomous vehicle 105. The autonomous control vehicle controlsubsystem may receive a course of action to be taken from theunder-chassis detection module 165 or the driving operation module 168of the VCU 150 and consequently provide instructions to other subsystemsto execute the course of action.

FIG. 2 shows a flow diagram 200 for the general operation of anautonomous vehicle (AV) safely in light of the health and surroundingsof the AV. Although this figure depicts functional steps in a particularorder for purposes of illustration, the process is not limited to anyparticular order or arrangement of steps. One skilled in the relevantart will appreciate that the various steps portrayed in this figurecould be omitted, rearranged, combined and/or adapted in various ways.

As shown in FIG. 2, the vehicle sensor subsystem 144 receives visual,auditory, or both visual and auditory signals indicating theenvironmental condition of the AV, as well as vehicle health or sensoractivity data are received in step 205. These visual and/or auditorysignal data are transmitted from the vehicle sensor subsystem 144 to thein-vehicle control computer system (VCU) 150, as in step 210. Any of thedriving operation module and the compliance module receive the datatransmitted from the vehicle sensor subsystem, in step 215. Then, one orboth of those modules determine whether the current status of the AV canallow it to proceed in the usual manner or that the AV needs to alterits course to prevent damage or injury or to allow for service in step220. The information indicating that a change to the course of the AV isneeded may include an indicator of sensor malfunction; an indicator of amalfunction in the engine, brakes, or other components necessary for theoperation of the autonomous vehicle; a determination of a visualinstruction from authorities such as flares, cones, or signage; adetermination of authority personnel present on the roadway; adetermination of a law enforcement vehicle on the roadway approachingthe autonomous vehicle, including from which direction; and adetermination of a law enforcement or first responder vehicle movingaway from or on a separate roadway from the autonomous vehicle. Thisinformation indicating that a change to the AV's course of action isneeded may be used by the compliance module to formulate a new course ofaction to be taken which accounts for the AV's health and surroundings,in step 225. The course of action to be taken may include slowing,stopping, moving into a shoulder, changing route, changing lane whilestaying on the same general route, and the like. The course of action tobe taken may include initiating communications with any oversight orhuman interaction systems present on the autonomous vehicle. The courseof action to be taken may then be transmitted from the VCU 150 to theautonomous control system, in step 230. The vehicle control subsystems146 then cause the autonomous truck 105 to operate in accordance withthe course of action to be taken that was received from the VCU 150 instep 235.

Autonomous Truck Oversight System

FIG. 3 illustrates a system 300 that includes one or more autonomousvehicles 105, a control center or oversight system 350 with a humanoperator 355, and an interface 362 for third-party 360 interaction. Ahuman operator 355 may also be known as a remoter center operator (RCO).Communications between the autonomous vehicles 105, oversight system 350and user interface 362 take place over a network 370. In some instances,where not all the autonomous vehicles 105 in a fleet are able tocommunicate with the oversight system 350, the autonomous vehicles 105may communicate with each other over the network 370 or directly. Asdescribed with respect to FIG. 1A, the VCU 150 of each autonomousvehicle 105 may include a module for network communications 178.

An autonomous truck may be in communication with an oversight system.The oversight system may serve many purposes, including: tracking theprogress of one or more autonomous vehicles (e.g., an autonomous truck);tracking the progress of a fleet of autonomous vehicles; sendingmaneuvering instructions to one or more autonomous vehicles; monitoringthe health of the autonomous vehicle(s); monitoring the status of thecargo of each autonomous vehicle in contact with the oversight system;facilitate communications between third parties (e.g., law enforcement,clients whose cargo is being carried) and each, or a specific,autonomous vehicle; allow for tracking of specific autonomous trucks incommunication with the oversight system (e.g., third-party tracking of asubset of vehicles in a fleet); arranging maintenance service for theautonomous vehicles (e.g., oil changing, fueling, maintaining the levelsof other fluids); alerting an affected autonomous vehicle of changes intraffic or weather that may adversely impact a route or delivery plan;pushing over the air updates to autonomous trucks to keep all componentsup to date; and other purposes or functions that improve the safety forthe autonomous vehicle, its cargo, and its surroundings.

An oversight system may also determine performance parameters of anautonomous vehicle or autonomous truck, including any of: data loggingfrequency, compression rate, location, data type; communicationprioritization; how frequently to service the autonomous vehicle (e.g.,how many miles between services); when to perform a minimal riskcondition (MRC) maneuver and monitoring the vehicle's progress duringthe MRC maneuver; when to hand over control of the autonomous vehicle toa human driver (e.g., at a destination yard); ensuring an autonomousvehicle performs or conforms to legal requirements at checkpoints andweight stations; give feedback regarding the identification of an objectover which an autonomous vehicle passes while in transit and it unableto identify with high certainty, and the like.

To allow for communication between autonomous vehicles in a fleet and anoversight system or command center, each autonomous vehicle may beequipped with a communication gateway. The communication gateway mayhave the ability to do any of the following: allow for AV to oversightsystem communication (i.e. V2C) and the oversight system to AVcommunication (C2V); allow for AV to AV communication within the fleet(V2V); transmit the availability or status of the communication gateway;acknowledge received communications; ensure security around remotecommands between the AV and the oversight system; convey the AV'slocation reliably at set time intervals; enable the oversight system toping the AV for location and vehicle health status; allow for streamingof various sensor data directly to the command or oversight system;allow for automated alerts between the AV and oversight system; complyto ISO 21434 standards; and the like.

An oversight system or command center may be operated by one or morehuman, also known as an operator or a remote center operator (RCO). Theoperator may set thresholds for autonomous vehicle health parameters, sothat when an autonomous vehicle meets or exceeds the threshold,precautionary action may be taken. An autonomous vehicle whose systemhealth data meets or exceeds a threshold set at the oversight system orby the operator may receive instructions that are automatically sentfrom the oversight system to perform the precautionary action.

The operator may be made aware of situations affecting one or moreautonomous vehicles in communication with or being monitored by theoversight system that the affected autonomous vehicle(s) may not beaware of Such situations may include: irregular or sudden changes intraffic flow (e.g., traffic jam or accident); emergency conditions(e.g., fire, sink-hole, bridge failure, dangerous debris along a route);large or ambiguous road debris (e.g., object unidentifiable by theautonomous vehicle); law enforcement activity on the roadway (e.g., carchase or road clearing activity); and the like. These types ofsituations that may not be detectable by an autonomous vehicle may bebrought to the attention of the oversight system operator throughtraffic reports, law enforcement communications, data from othervehicles that are in communication with the oversight system, reportsfrom drivers of other vehicles in the area, and similar distributedinformation venues. An autonomous vehicle may not be able to detect suchsituations because of limitations of sensor systems (e.g., unable toobtain a clear image or inability of analysis module to confidentlyidentify an object in an image) or lack of access to the informationdistribution means (e.g., no direct communication with weather agency).An operator at the oversight system may push such information toaffected autonomous vehicles that are in communication with theoversight system. The affected autonomous vehicles may proceed to altertheir route, trajectory, or speed in response to the information pushedfrom the oversight system. In some instances, the information receivedby the oversight system may trigger a threshold condition indicatingthat MRC (minimal risk condition) maneuvers are warranted;alternatively, or additionally, an operator may evaluate a situation anddetermine that an affected autonomous vehicle should perform a MRCmaneuver and subsequently send such instructions to the affectedvehicle. In these cases, each autonomous vehicle receiving eitherinformation or instructions from the oversight system or the oversightsystem operator uses its on-board computing unit (i.e. VCU) to determinehow to safely proceed, including performing a MRC maneuver that includespulling-over or stopping.

An oversight system or command center may allow a third party tointeract with the oversight system operator, with an autonomous truck,or with both the human system operator and an autonomous truck. A thirdparty may be a customer whose goods are being transported, a lawenforcement or emergency services provider, or a person assisting theautonomous truck when service is needed.

Method for Operating an Autonomous Truck

A method for operating an autonomous truck with an under-chassis objectdetection system may include the data transmission and processing bymodules on the autonomous truck and/or by an oversight system. Theunder-chassis object detection subsystem of an autonomous truck senses asmall object or imperfection on a road over which the autonomous truckis travelling. The signal data from the under-chassis object detectionsubsystem are transmitted from the under-chassis object detectionsubsystem to the in-vehicle control computer system (VCU). In thein-vehicle control computer system, the under-chassis object detectionmodule receives the data transmitted from the under-chassis objectdetection system. Then, the under-chassis object detection moduleproduces passes information about the small object detected to othercomponents of the VCU to formulate a course of action to be taken. Thecourse of action to be taken may include maintaining speed anddirection, slowing, stopping, moving into a shoulder, changing route,changing lane while staying on the same general route, and the like. Thecourse of action to be taken may include initiating communications withany oversight or human interaction systems present on the autonomousvehicle. The course of action to be taken is then transmitted from theVCU 150 to the various vehicle control subsystems. The vehicle controlsubsystems then cause the autonomous truck to operate in accordance withthe course of action to be taken that was received from the VCU.

FIG. 4 shows a flow diagram 400 for a method for operating an autonomousvehicle, particularly an autonomous truck, with an under-chassis objectdetection system and an on-board computing unit with an under-chassisdetection module. The under-chassis object detection system includes oneor more sensors that monitor an area that includes part of the roadwayunder the chassis of the autonomous vehicle. In the case of anautonomous truck, that could include the area under the tractor chassisor under the trailer. Visual data, sensor data, including point clouddata, is obtained by sensors with detection areas that include under thevehicle chassis in step 405 of the shown method. This data is sent fromthe sensor(s) to the under-chassis detection module and objects areidentified by the module in step 415. The identified objects can includesmall objects on the surface of the roadway or imperfections in theroadway. A determination may be made about the certainty with which theunder-chassis detection module is able to identify an object from thesensor data. When the certainty level of the object identification isbelow a threshold amount, the autonomous vehicle may contact anoversight system (e.g., remote control center) and send the sensor datafor object identification, as in step 418. The oversight system may havea remote operator (RCO, described above), who can identify an object ormultiple object from the sensor data. The identified objects are sentfrom the oversight system, or remote control center, back to theautonomous vehicle. Alternatively, when the under-chassis detectionmodule is able to identify an object on the roadway from the sensordata, information about the identified object can be used by theunder-chassis detection module to determine a hazard level of theidentified object directly. Once the under-chassis detection module hasinformation about the identified object on the road from either theoversight system or based on the identification made by the module, ahazard level of the identified object may be made, as in step 420. Thehazard level determination may include determining whether theidentified object fulfills the following criteria. When any of thecriteria is met, then a change in the trajectory of the autonomousvehicle, either the velocity or path, may be needed. When none of thecriteria are met, then no change in trajectory of the autonomous vehicleis needed and the under-chassis object detection subsystem continues toprovide sensor data to the system. A criteria used to evaluate hazardlevel is that the identified object on the road surpasses apredetermined size threshold, shown in step 420 a. Another criteria isthat the identified object on the road is located or situated such thata change in vehicle trajectory, either or both speed and direction, isneeded in step 420 b. A third criteria is that the identified object onthe road is sharp, jagged, or otherwise a potential cause of a punctureor other damage to the underside of the vehicle or the tires, as in step420 c. Once the hazard level determination has been made by theunder-chassis detection module, this module will indicate to variousmodule of the VCU that a change in the trajectory or action of theautonomous vehicle is needed. In step 425, the modules of the VCUreceiving the information from the under-chassis object detection modulethat a change of action by the autonomous vehicle is needed will thenproceed to determine, calculate, or formulate a course of action to betaken. Alternatively, the under-chassis object detection module mayindicate to the autonomous driving unit of the control subsystems that achange of trajectory or action is needed, and the autonomous drivingunit (e.g., autonomous control unit) may formulate or determine thecourse of action to be taken. The course of action to be taken inresponse to the identified object on the road may then be implemented,as in step 435, by one or more vehicle control subsystems of theautonomous vehicle. The vehicle control subsystems which may allow theautonomous vehicle to avoid or compensate for the presence of theidentified object on the road may include any of: an engine power outputunit, a braking unit, a navigation unit, a steering system, and anautonomous control unit. While the autonomous vehicle proceeds on theroad, either in response to a detected object on the road or accordingto the safest manner to proceed on its route absent road debris orimperfections, the under-chassis detection subsystem will continue tocollect data and pass it to the under-chassis detection module foranalysis.

When encountering road debris or object which the autonomous truck maypass over, the under-chassis object detection module may identify orclassify objects based on size or dimensions. Object that may bedetected by an autonomous truck with an under-chassis object detectionsubsystem and an under-chassis object detection module include: tiretreads, small objects, medium objects, small pedestrians, static object,moving objects, an object that could be detected by one or more sensorsmounted under the fifth wheel of tractor-trailer, and the like.

An autonomous truck as described herein may be able to detect andclassify tire treads on the roadway that are taller than a firstpredetermined dimension (e.g., 10 cm (3.94 in), 15 cm (5.91 in.), 20 cm(8 in)) or longer than a second predetermined dimension (e.g., 15 cm(5.91 in), 30 cm (11.8 in.), 45 cm (17.7 in)) from at least apredetermined distance (e.g., from at least 90 meters, 100 meters, 110meters, 120 meters) on the autonomous truck's projected path of traveland on any lane or shoulder adjacent to that path using data from all ofthe sensor subsystems of the autonomous truck.

The autonomous truck may be able to detect objects with height betweentwo predetermined lengths (e.g., between 10 cm (3.94 in.) and 15 cm(5.91 in.), between 15 cm (5.91 in.), 20 cm (8 in)) from at least apredetermined distance on autonomous truck's projected path of travel(e.g., from at least 70 m, 80 m, 90 m, 100 m, 110 m, 120 m) and on anylane or shoulder adjacent to the path of the autonomous truck using datafrom all of the sensor subsystems of the autonomous truck; such objectmay be classified by the autonomous truck as a small object. A smallobject may be any of: an animal, remains of an animal, a conveyance,parts of a conveyance, a box, a bag of any content, and any debris thatconforms to the predetermined size range for a small object.

The autonomous truck may be able to detect objects with height betweentwo predetermined lengths (e.g., between 15 cm (5.91 in.) and 25 cm(9.81 in.), 20 cm (8 in) and 30 cm (11.8 in)) from at least apredetermined distance on the autonomous truck's projected path oftravel (e.g., from at least 70 m, 80 m, 90 m, 100 m, 110 m, 120 m) andon any lane or shoulder adjacent to the path of the autonomous truckusing data from all of on-vehicle the sensor subsystems; such an objectmay be determined to be a medium-sized object. A medium-sized object maybe any of: an animal, remains of an animal, a conveyance, parts of aconveyance, a ladder, a box, a disabled conveyance, a bag of anycontent, and any debris that conforms to the predetermined size rangefor a medium-sized object.

An autonomous truck may be able to detect objects with height betweentwo predetermined lengths (e.g., between 25 cm (9.81 in.) and 40 cm(15.75 in.), between 30 cm (11.8 in) and 50 cm (19.62 in)) from at leasta predetermined distance on the projected path of travel (e.g., from atleast 100 m, 110 m, 120 m, 130 m, 140 m) and on any lane or shoulderadjacent to the autonomous truck's path; such an object may beidentified as a large object. A large object may be any of: an animal,remains of an animal, a conveyance, parts of a conveyance, a ladder, abox, a disabled conveyance, a bag of any content, and any debris thatconforms to the predetermined size range for a large object.

Additionally, or optionally, an autonomous truck may identify anextra-large object as an object with a height greater than apredetermined length (e.g., greater than 40 cm (15.75 in.) from morethan a distance that is far enough to allow the autonomous truck to cometo a complete stop or a predetermined distance (e.g., 125 meters, 150meters, 175 meters) whichever distance is greater. An extra-large objectmay be any of: an animal, remains of an animal, a conveyance, parts of aconveyance, a ladder, a box, a disabled conveyance, a skateboard, abicycle, a motorcycle, a scooter, a bag of any content, and any debristhat conforms to the predetermined size threshold for an extra-largeobject.

In response to identifying an object, an autonomous truck may alter itstrajectory, stop all together, or determine that it is safe to proceedalong its original path or route. In some implementations, when anobject is detected in the path of the autonomous truck (e.g., autonomousvehicle), the autonomous truck may come to a complete stop beforereaching the detected object. Alternatively, or additionally, theautonomous truck may slow down before reaching the detected object.Further, a static or moving object of a predetermined heightapproximating the height of a two-year old human, such as about 32inches (0.8128 meters), including about 34 inches, 36 inches, and even37 inches detected by the autonomous truck may cause the autonomoustruck to change lanes, slow down, stop before reaching the object, orotherwise alter trajectory (e.g., speed and/or direction). Theautonomous truck may preferably avoid coming into contact with anymoving unknown objects, excluding flying debris. For detected staticobjects, an autonomous truck may straddle, or pass over, object whichare shorter than the ground clearance of the truck's front bumper andnarrower than the minimum wheel inside spacing across all of theautonomous truck's axles. Further, an autonomous truck may be able toidentify when it impacts an object, and whether or not the object causesdamage to the autonomous truck. Damage may include vehicular bodydamage, a loss of tire pressure, a loss of fuel pressure, a loss of oilpressure, and any other mechanical or electrical deviation from normaloperating conditions. Additionally, an autonomous truck may contact anoversight system, or a remote control operator, when the autonomoustruck collides with an object or notes debris in the roadway. Thisinformation may be relayed to trucks that have yet to pass over thatportion of the roadway by either the oversight system or the autonomoustruck that first encountered the debris.

It should be understood that the specific order or hierarchy of steps inthe processes disclosed herein is an example of exemplary approaches.Based upon design preferences, it is understood that the specific orderor hierarchy of steps in the processes may be rearranged while remainingwithin the scope of the present disclosure. The accompanying methodclaims present elements of the various steps in a sample order and arenot meant to be limited to the specific order or hierarchy presented.

While several embodiments have been provided in this disclosure, itshould be understood that the disclosed systems and methods might beembodied in many other specific forms without departing from the spiritor scope of this disclosure. The present examples are to be consideredas illustrative and not restrictive, and the intention is not to belimited to the details given herein. For example, the various elementsor components may be combined or integrated in another system or certainfeatures may be omitted, or not implemented.

The description and figures of this document include tractor-trailertype vehicles. The methods and systems described herein may apply to orinclude other autonomous vehicles that operate on roadways, includingother towing vehicles, passenger vehicles, and the like.

The description and figures of this document may utilize acronyms forsensor systems including GPS, LIDAR, LiDAR, radar, Radar, IMU (inertialmeasurement unit), and the like. For acronyms which there is adifference in capitalization (e.g., LIDAR, LiDAR, lidar), these acronymsshould not be limited to any one specific variety of sensing technology,but rather may encompass the various types of sensing technologiesgenerally associated with each acronym.

In addition, techniques, systems, subsystems, and methods described andillustrated in the various embodiments as discrete or separate may becombined or integrated with other systems, modules, techniques, ormethods without departing from the scope of this disclosure. Other itemsshown or discussed as coupled or directly coupled or communicating witheach other may be indirectly coupled or communicating through someinterface, device, or intermediate component whether electrically,mechanically, or otherwise. Other examples of changes, substitutions,and alterations are ascertainable by one skilled in the art and could bemade without departing from the spirit and scope disclosed herein.

What is claimed is:
 1. A system, comprising: an autonomous vehiclecomprising: an under-chassis object detection subsystem; an in-vehiclecontrol computer comprising: an under-chassis object detection module;and an autonomous control subsystem.
 2. The system of claim 1 whereinthe autonomous vehicle comprises a tractor-trailer and the under-chassisobject detection subsystem comprises a sensor mounted under a fifthwheel of a tractor portion of the tractor-trailer.
 3. The system ofclaim 2, wherein the sensor comprises any of: a light detection andranging unit, a radar unit, and a camera.
 4. The system of claim 1,wherein the under-chassis object detection subsystem comprises one ormore sensors with a detection area that includes part of an area of aroad under a chassis of the autonomous vehicle.
 5. The system of claim4, wherein the one or more sensors of the under-chassis object detectionsubsystem comprises any of: a light detection and ranging unit, a radarunit, and a camera.
 6. The system of claim 1, further comprising acommand center configured to receive data from the autonomous vehicle,the data comprising sensor data from any of: the under-chassis objectdetection subsystem and the under-chassis object detection module. 7.The system of claim 1, further comprising a driving operation moduleconfigured to: receive data from the under-chassis object detectionmodule; and plan trajectory changes for the autonomous vehicle inresponse to objects detected and identified as hazardous by theunder-chassis object detection module.
 8. The system of claim 7, furthercomprising one or more vehicle control subsystems, each vehicle controlsubsystem configured to accept operating commands from the drivingoperation module, the one or more vehicle control subsystems comprisingany of: an engine power output unit, a braking unit, a navigation unit,a steering unit, and an autonomous control unit.
 9. The system of claim1, further comprising an autonomous control unit configured to: accepthazard information from the under-chassis object detection module; plana trajectory change for the autonomous vehicle in response to the hazardinformation; and send, based on the planned trajectory change, operatingcommands to one or more vehicle control subsystems, the one or morevehicle control subsystems comprising any of: an engine power outputunit; a braking unit; a navigation unit; and a steering unit.
 10. Amethod, comprising: sensing, by a sensor of an under-chassis objectdetection subsystem, an object on a road that an autonomous vehicle istravelling upon; transmitting, by the under-chassis object detectionsubsystem, data from the sensor to an in-vehicle control computer; anddetermining, by an under-chassis object detection module of thein-vehicle control computer, the object on the road, the object being ofa size that allows a chassis of the autonomous vehicle to pass over theobject on the road.
 11. The method of claim 10, further comprisingmodifying a trajectory or route of the autonomous vehicle to account forthe object on the road.
 12. The method of claim 10, further comprisingdetermining, by the under-chassis object detection module, a hazardlevel for the object on the road.
 13. The method of claim 12, furthercomprising modifying, based on the hazard level for the object on theroad, a trajectory or route of the autonomous vehicle.
 14. The method ofclaim 12, wherein determining a hazard level for the object on the roadcomprises: determining a certainty value for an identification of theobject on the road; sending data to an oversight system when thecertainty value is below a threshold value; and identifying, by theoversight system, the object on the road with certainty.
 15. The methodof claim 14, wherein identifying the object on the road with certaintycomprises receiving a determination from a human remote controloperator.
 16. The method of claim 12, wherein determining a hazard levelfor the object on the road comprises: determining, by the under-chassisobject detection module, that the object on the road is larger than apredetermined threshold size; determining, by the under-chassis objectdetection module, that the object on the road is situated in a positionthat requires a change in trajectory by the autonomous vehicle; anddetermining, by the under-chassis object detection module, that theobject on the road is sharp, jagged, or otherwise a potential cause of apuncture or other damage to an underside of the autonomous vehicle orany tires of the autonomous vehicle.
 17. The method of claim 12, furthercomprising causing the autonomous vehicle to operate according to adetermined course of action that is based on the hazard level determinedfor the object on the road.
 18. The method of claim 11, furthercomprising causing the autonomous vehicle to execute the trajectory orroute that is modified based on the presence of the object on the road.19. An autonomous vehicle comprising an in-vehicle computing unitcomprising: at least one processor; and at least one memory includinginstructions which, when executed by the at least one processor, causethe at least one processor to execute a method, the method comprising:sensing, by a sensor of an under-chassis object detection subsystem, anobject on a road that an autonomous vehicle is travelling upon;transmitting, by the under-chassis object detection subsystem, data fromthe sensor to the in-vehicle control computer; and determining, by anunder-chassis object detection module of the in-vehicle controlcomputer, the object on the road, the object being of a size that allowsa chassis of the autonomous vehicle to pass over the object on the road.20. The autonomous vehicle of claim 19, wherein the at least one memoryfurther includes instructions which cause the processor to: modify atrajectory or route of the autonomous vehicle to account for the objecton the road; and determine a hazard level for the object on the roaddetermined by the under-chassis object detection module.